wayneong95 / udacity-capstone

A capstone project for the Udacity Data Scientist Nanodegree

Table of Contents

1. Installation
2. Project Summary
3. File Descriptions
4. Summary of Results

Installation

There should be no necessary libraries to run the code here beyond the Anaconda distribution of Python. The code should run with no issues using Python versions 3.*.

Libraries used: Pandas Numpy Math Json Matplotlib Sklearn

Project Summary

A Capstone Project on the Starbucks dataset for the Udacity Data Scientist Nanodegree program. This project aims to develop a machine learning model that classifies whether a user will be responsible to a certain type of offer, based on several independent variables.

File Descriptions

There are three datasets - portfolio.json, profile.json and transcript.json.

portfolio.json — Contains offer ids and meta data about each offer (duration, type, etc) profile.json — Demographic data for each custmer transcript.json — Records for transactions, offers received, offers viewed, and offers completed

All data files are located in "data files.zip".

Summary of Results

The resulting model using Random Forest Classifier was able to correctly classify a customer 68.3% of the time. The best model was determined using cross validation score and grid search CV to determine the best parameters for this classifier.

The main findings of the code can be found at the post available here.